---
title: CI/CD Pipelines
summary: Detailed overview of the CI/CD pipelines used to deploy and maintain the FlowMart e-commerce platform
sidebar:
    label: 04 - CI/CD Pipelines
    order: 4
---

# CI/CD Pipelines

This document provides an overview of the Continuous Integration (CI) and Continuous Deployment (CD) pipelines used to build, test, and deploy the FlowMart e-commerce platform.

## CI/CD Philosophy

Our CI/CD approach follows these key principles:

1. **Automation First**: Automate everything that can be automated
2. **Fast Feedback**: Provide developers with quick feedback on their changes
3. **Consistency**: Ensure consistent builds and deployments across all environments
4. **Security**: Integrate security testing throughout the pipeline
5. **Observability**: Monitor and track all deployments and their impacts
6. **Self-service**: Enable teams to deploy independently, but safely

## CI/CD Technology Stack

Our CI/CD pipeline utilizes the following key technologies:

| Technology | Purpose |
|------------|---------|
| GitHub Actions | Main CI/CD orchestration platform |
| ArgoCD | Kubernetes GitOps deployment tool |
| Helm | Kubernetes package management |
| Docker | Container building and registry |
| Terraform | Infrastructure as Code deployment |
| SonarQube | Code quality and security analysis |
| Jest, JUnit, pytest | Unit testing frameworks |
| Playwright | End-to-end testing |
| K6 | Performance testing |
| OWASP ZAP | Security scanning |
| Snyk | Dependency vulnerability scanning |
| AWS ECR | Container registry |

## CI/CD Pipeline Overview

Our CI/CD pipeline consists of multiple stages with specific responsibilities:

```mermaid
flowchart TD
    classDef build fill:#dae8fc,stroke:#6c8ebf,stroke-width:2px
    classDef test fill:#d5e8d4,stroke:#82b366,stroke-width:2px
    classDef deploy fill:#ffe6cc,stroke:#d79b00,stroke-width:2px
    classDef release fill:#f8cecc,stroke:#b85450,stroke-width:2px

    CodePush[Code Push] --> Build[Build & Package]
    Build --> UnitTest[Unit Tests]
    UnitTest --> CodeQuality[Code Quality Analysis]
    CodeQuality --> SecurityScan[Security Scanning]
    SecurityScan --> DockerBuild[Docker Build]
    DockerBuild --> PushRegistry[Push to Registry]
    PushRegistry --> DeployDev[Deploy to Dev]
    DeployDev --> IntegrationTest[Integration Tests]
    IntegrationTest --> DeployStaging[Deploy to Staging]
    DeployStaging --> PerformanceTest[Performance Tests]
    DeployStaging --> E2ETest[End-to-End Tests]
    PerformanceTest --> Approval{Approval}
    E2ETest --> Approval
    Approval -->|Approved| DeployProd[Deploy to Production]
    Approval -->|Rejected| Feedback[Feedback Loop]
    DeployProd --> SmokeTest[Smoke Tests]
    SmokeTest --> Monitoring[Monitoring & Observability]
    
    class Build,DockerBuild build
    class UnitTest,CodeQuality,SecurityScan,IntegrationTest,PerformanceTest,E2ETest,SmokeTest test
    class DeployDev,DeployStaging,DeployProd deploy
    class Approval,Monitoring release
```

## Pipeline Stages in Detail

### 1. Build & Package

- Triggered by code push or pull request
- Compiles application code
- Installs dependencies using package managers (npm, Maven, pip)
- Generates build artifacts
- Built in isolated environments with cached dependencies

```yaml
# Example GitHub Actions code snippet
build:
  runs-on: ubuntu-latest
  steps:
    - uses: actions/checkout@v3
    - name: Set up Node.js
      uses: actions/setup-node@v3
      with:
        node-version: '16'
        cache: 'npm'
    - name: Install dependencies
      run: npm ci
    - name: Build
      run: npm run build
    - name: Upload build artifacts
      uses: actions/upload-artifact@v3
      with:
        name: build-artifacts
        path: build/
```

### 2. Test

Multiple types of tests run in parallel to provide rapid feedback:

- **Unit Tests**: Test individual components in isolation
- **Integration Tests**: Test component interactions
- **End-to-End Tests**: Test complete user flows
- **Performance Tests**: Test application performance under load
- **Security Tests**: Scan for vulnerabilities in code and dependencies

```mermaid
flowchart LR
    subgraph "Test Phase"
        direction TB
        Unit[Unit Tests]
        Integration[Integration Tests]
        E2E[End-to-End Tests]
        Performance[Performance Tests]
        Security[Security Tests]
    end
    
    CodeBase[Code Base] --> Unit
    CodeBase --> Integration
    CodeBase --> E2E
    CodeBase --> Performance
    CodeBase --> Security
    
    Unit --> Results[Test Results]
    Integration --> Results
    E2E --> Results
    Performance --> Results
    Security --> Results
```

### 3. Docker Build & Registry Push

- Builds Docker images for all services
- Tags images with git commit SHA and environment
- Pushes images to AWS ECR
- Scans images for vulnerabilities before pushing

```yaml
# Example GitHub Actions code snippet
docker-build:
  runs-on: ubuntu-latest
  needs: [build, test]
  steps:
    - uses: actions/checkout@v3
    - name: Configure AWS credentials
      uses: aws-actions/configure-aws-credentials@v1
      with:
        aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
        aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
        aws-region: us-west-2
    - name: Login to Amazon ECR
      id: login-ecr
      uses: aws-actions/amazon-ecr-login@v1
    - name: Build and push Docker image
      uses: docker/build-push-action@v4
      with:
        context: .
        push: true
        tags: ${{ steps.login-ecr.outputs.registry }}/flowmart-orders-service:${{ github.sha }}
```

### 4. Deployment

We use GitOps with ArgoCD for managing deployments:

- **Development**: Automatic deployment on successful build
- **Staging**: Automatic deployment after integration tests pass
- **Production**: Manual approval required, then automated deployment

```mermaid
sequenceDiagram
    participant Dev as Developer
    participant GH as GitHub Actions
    participant Reg as Container Registry
    participant Git as Git Repo (Manifests)
    participant Argo as ArgoCD
    participant K8s as Kubernetes Cluster
    
    Dev->>GH: Push Code
    GH->>GH: Build & Test
    GH->>Reg: Push Container Image
    GH->>Git: Update Image Tag in Manifests
    Git->>Argo: Sync (Automatic or Manual)
    Argo->>K8s: Apply Manifests
    K8s->>K8s: Deploy Application
    K8s->>Argo: Report Status
    Argo->>Git: Update Deployment Status
```

### 5. Post-Deployment Verification

- **Smoke Tests**: Quick tests to verify basic functionality
- **Canary Deployment**: Rolling deployment with traffic shifting
- **Monitoring**: Performance and error tracking during and after deployment

## Infrastructure Pipeline

For infrastructure changes, we have a separate pipeline:

```mermaid
flowchart TD
    InfraChange[Infrastructure Change] --> TerraformPlan[Terraform Plan]
    TerraformPlan --> AutoReview[Automated Review]
    AutoReview --> HumanReview[Human Review]
    HumanReview --> Approval{Approved?}
    Approval -->|Yes| TerraformApply[Terraform Apply]
    Approval -->|No| Feedback[Feedback Loop]
    TerraformApply --> Verification[Infrastructure Verification]
    Verification --> Documentation[Update Documentation]
```

## Feature Branch Workflow

We follow a feature branch workflow for development:

```mermaid
gitGraph
    commit
    commit
    branch feature/order-tracking
    checkout feature/order-tracking
    commit
    commit
    commit
    checkout main
    merge feature/order-tracking
    branch feature/payment-gateway
    checkout feature/payment-gateway
    commit
    commit
    checkout main
    merge feature/payment-gateway
    commit
```

## Deployment to Multiple Environments

Our pipeline handles deployments to multiple environments:

```mermaid
flowchart TD
    Build[Build & Test] --> DevDeploy[Deploy to Dev]
    
    DevDeploy --> IntegrationTest[Run Integration Tests]
    IntegrationTest -->|Pass| StagingDeploy[Deploy to Staging]
    IntegrationTest -->|Fail| FixIssues[Fix Issues]
    FixIssues --> Build
    
    StagingDeploy --> StagingTests[Run E2E & Performance Tests]
    StagingTests -->|Pass| ApprovalGate{Approval Gate}
    StagingTests -->|Fail| FixIssues
    
    ApprovalGate -->|Approved| ProdDeploy[Deploy to Production]
    ApprovalGate -->|Rejected| FixIssues
    
    ProdDeploy --> CanaryDeploy[Canary Deployment]
    CanaryDeploy --> Monitor[Monitor]
    Monitor -->|Healthy| FullRollout[Full Rollout]
    Monitor -->|Issues| Rollback[Rollback]
```

## Rollback Strategy

In case of deployment issues, we have an automated rollback strategy:

1. **Immediate Automated Rollback**: Triggered by health checks or error rate spikes
2. **One-Click Manual Rollback**: Available through the deployment dashboard
3. **Previous Version Restoration**: Reverts to the last known good state

```mermaid
sequenceDiagram
    participant Metrics as Metrics System
    participant CD as CD Pipeline
    participant Git as Git Repository
    participant K8s as Kubernetes
    
    Note over Metrics,K8s: New deployment shows issues
    Metrics->>CD: Alert on error threshold exceeded
    CD->>CD: Trigger rollback process
    CD->>Git: Revert to previous manifest version
    Git->>K8s: Apply previous manifests
    K8s->>K8s: Restore previous deployment
    K8s->>CD: Report successful rollback
    CD->>Metrics: Verify metrics returning to normal
```

## Pipeline Security

Security is integrated throughout our pipeline:

- **Secrets Management**: Secrets stored in AWS Secrets Manager and injected at runtime
- **SAST**: Static Application Security Testing integrated in build phase
- **DAST**: Dynamic Application Security Testing during staging deployment
- **Dependency Scanning**: Checks for vulnerable dependencies
- **Container Scanning**: Scans container images for vulnerabilities
- **Infrastructure Scanning**: Checks IaC for security misconfigurations

## Observability

Our pipeline provides comprehensive observability:

- **Deployment Tracking**: Each deployment is traced from commit to production
- **Metrics Collection**: Performance metrics before and after deployment
- **Log Aggregation**: Centralized logging for all pipeline stages
- **Alerting**: Automated alerts for pipeline failures or anomalies
- **Dashboards**: Visual representation of pipeline health and history

Example deployment dashboard:

```mermaid
gantt
    title Recent Deployments Timeline
    dateFormat  YYYY-MM-DD HH:mm
    axisFormat %H:%M
    
    section Orders Service
    Build #452           :a1, 2023-05-10 09:00, 5m
    Deploy to Dev        :a2, after a1, 10m
    Integration Tests    :a3, after a2, 15m
    Deploy to Staging    :a4, after a3, 10m
    E2E Tests            :a5, after a4, 30m
    Deploy to Prod       :a6, after a5, 15m
    
    section Inventory Service
    Build #389           :b1, 2023-05-10 10:00, 5m
    Deploy to Dev        :b2, after b1, 10m
    Integration Tests    :b3, after b2, 15m
    Deploy to Staging    :b4, after b3, 10m
    E2E Tests            :b5, after b4, 30m
    
    section Payment Service
    Build #421           :c1, 2023-05-10 08:30, 5m
    Deploy to Dev        :c2, after c1, 10m
    Integration Tests    :c3, after c2, 15m
    Deploy to Staging    :c4, after c3, 10m
    E2E Tests            :c5, after c4, 30m
    Deploy to Prod       :c6, after c5, 15m
```

## Continuous Improvement

We continuously improve our pipeline through:

1. **Pipeline Metrics**: Track build times, success rates, and deployment frequency
2. **Postmortems**: Document and learn from deployment failures
3. **Automation Improvements**: Regularly identify manual steps for automation
4. **Cross-team Learning**: Share best practices across development teams

## Conclusion

Our CI/CD pipeline provides a robust, secure, and efficient process for deploying changes to the FlowMart platform. By automating the build, test, and deployment processes, we can deliver new features and bug fixes to users quickly and reliably while maintaining high quality standards. 